Alumni Jin Wu Published His Research Finding on Photosynthetic Rainforest in Science
Alumni Jin Wu and his colleagues have published their study Leaf development and demography explain photosynthetic seasonality in the Amazon evergreen forest,in the journal Science. This has been the cover story of the publication on February 26th.
Although the Amazon rainforest is evergreen, its photosynthesis rate changes from season to season. Significantly, the rate will increase in the dry season. However, this phenomenon is rather arguable among academics. Some scientists presume that exposure to more sunlight in the dry season can contribute to a growth of photosynthesis rate in the whole forest system, considering there is no shortage of surface water in the rainforest.
Wu's paper proved that the seasonal variation resulted from the dynamic changes of the rainforest’s internal structure. His team found that more than 80% of the forest canopy changed in different seasons, among which over 50% emerged in dry weather. The leafage of the forest was getting younger, which brought about the seasonal variations of photosynthetic changes in the rainforest, because new leaves were born and old leaves faded. This study has enabled us to take greater advantage of the earth system process model so as to simulate carbon cycling process of the whole rainforest, and be more effective in discussing the influence that rainforest has on the current climate change.
Jin Wu, graduated in Geographical Information System from the School of Resources and Environmental Sciences in 2007. After graduation he was recommended to further his study for master degree in the School of Resources Science and Technology in Beijing Normal University and received doctorate of Ecology and Evolutionary Biology from University of Arizona in 2015. Currently, he is doing his post-doctoral research in Brookhaven National Laboratory, focusing on the process of terrestrial ecosystem and its response and impact on the climate change.
(Rewritten by Xiaopei Dai, Edited by Mengtian Wang, Mark & Sijia Hu)